Systems For Summarizing Contact Center Calls And Methods Of Using Same

ABSTRACT

A method for creating a textual summary of a call includes transcribing speech to text in real time using a speech-to-text generating unit configured for execution upon one or more data processors, automatically matching, in real-time, text to predetermined intents and extracted entities using an intent recognizing unit for execution upon the one or more data processors, automatically mapping the predetermined intents and extracted entities into a call summary using one or more mapping functions, and displaying the call summary using an agent user interface for execution upon the one or more data processors. A contact center call summarization system may include a contact center communication device, a speech-to-text generating unit, an intent recognizing unit, and an agent user interface.

CROSS-REFERENCE TO RELATED APPLICATION

This application claims the benefit of U.S. Provisional PatentApplication No. 63/057,931, filed on Jul. 29, 2020, which is herebyincorporated by reference in its entirety for all purposes.

BACKGROUND 1. Field

The present disclosure relates to systems for summarizing contact centercalls, and methods thereof. For example, systems for summarizing contactcenter calls may include an agent or customer communication unit, aspeech-to-text generating unit, an intent recognizing unit, an agentuser interface, and an intent configuration unit. A method of using thesystem may include transcribing speech to text, matching text to intentsand extracted entities, and mapping intents and associated entities to areadable summary using a mapping function.

2. Description of Related Art

Contact center agents are often asked to prepare a summary of calls thatthey take with customers. These summaries are used for many purposessuch as providing a summary to a different agent when the customer callsback in the future. They can also be used for analytics. Unfortunately,many agents do not produce these summaries because they take time tocreate and agents face pressure to talk to customers rather than createcall summaries. Even when such call summaries are created, they areoften incomplete or inaccurate. They can also vary in style from agentto agent making it difficult for an agent to read a summary written byanother agent.

Traditional methods for summarizing contact center calls typicallyinclude transcribing audio recordings of the contact center call, andusing the transcribed text information as a summary of the call. Othersolutions may include incorporating an entire transcript of a contactcenter call into a database such as a customer relationship managementsystem. However, these approaches are tedious because they require anagent to read an entire transcript, which can be lengthy and difficultto comprehend.

Other methods for summarizing contact center calls may apply artificialintelligence (hereinafter “AI”) techniques for text summarization. Thisis common for natural language processing systems, and is widely usedfor techniques like producing a summary of a news article or selectinghighlights from an article. Unfortunately, these techniques do not workwell on transcripts of contact center calls. Human to humanconversations are much less structured than a written document.Transcripts of contact center calls also typically include errors due tothe inaccuracies of speech recognition. These problems with traditionalnatural language processing text summarization techniques make them nota good fit for use with contact center call summarization.

SUMMARY

This Summary is provided to introduce a selection of concepts in asimplified form that are further described below in the DetailedDescription. This Summary is not intended to identify key features oressential features of the invention, nor is it intended to be used as anaid in determining the scope of the claims.

In an aspect, a method for creating a textual summary of a call includestranscribing speech to text in real time using a speech-to-textgenerating unit configured for execution upon one or more dataprocessors; automatically matching, in real-time, text to predeterminedintents and extracted entities using an intent recognizing unit forexecution upon the one or more data processors; automatically mappingthe predetermined intents and extracted entities into a call summaryusing one or more mapping functions; and displaying the call summaryusing an agent user interface for execution upon the one or more dataprocessors.

A contact center call summarization system for generating a contactcenter call summary includes a contact center communication deviceconfigured to communicate with a customer communication device via anetwork; a speech-to-text generating unit configured for execution uponone or more data processors and configured to convert speech of acustomer communication into text; an intent recognizing unit forexecution upon the one or more data processors and configured to receivetranscribed speech from the speech-to-text generating unit and usemachine learning to match speech to intents and entities; an intentconfiguration unit for execution upon the one or more data processorsand configured to update or create intents, entities, and associatedtraining phrases for the intent recognizing unit; and an agent userinterface for execution upon the one or more data processors andconfigured to display a call summary received from the intentrecognizing unit to allow an agent to edit, replace, reorder, delete, orconfirm text segments, intents, or entities of the call summary.

Other features and aspects may be apparent from the following detaileddescription and the drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

The foregoing summary, as well as the following detailed description,will be better understood when read in conjunction with the appendeddrawings. For the purpose of illustration, certain examples of thepresent description are shown in the drawings. It should be understood,however, that the invention is not limited to the precise arrangementsand instrumentalities shown. The accompanying drawings, which areincorporated in and constitute a part of this specification, illustratean implementation of system, apparatuses, and methods consistent withthe present description and, together with the description, serve toexplain advantages and principles consistent with the invention.

FIG. 1 is a diagram illustrating an example of a system for summarizingcontact center calls.

FIG. 2 is a diagram illustrating an example of a user interface displaythat includes a call summary generated using the system of FIG. 1.

FIGS. 3A, 3B, and 3C are diagrams illustrating examples of userinterfaces that allow an agent to confirm or edit a call summarygenerated using the system of FIG. 1.

FIGS. 4A, 4B, 4C, and 4D are diagrams illustrating examples of userinterfaces that allow an agent to remove false positives in a callsummary generated using the system of FIG. 1.

FIGS. 5A, 5B, 5C, 5D, 5E, 5F, 5G, 5H are diagrams illustrating examplesof user interfaces that allow an agent to update entities in a callsummary generated using the system of FIG. 1.

FIGS. 6A, 6B, and 6C are diagrams illustrating examples of userinterfaces that allow an agent to reorder a call summary generated usingthe system of FIG. 1.

FIGS. 7A, 7B, and 7C are diagrams illustrating examples of userinterfaces that allow an agent to add missing intents to a call summarygenerated using the system of FIG. 1

FIG. 8 is a diagram illustrating an example of a method for summarizingcontact center calls using the system of FIG. 1.

FIG. 9 is a block diagram of an example system for summarizing contactcenter calls.

FIG. 10 is a block diagram of an example computer system for summarizingcontact center calls.

Throughout the drawings and the detailed description, unless otherwisedescribed, the same drawing reference numerals will be understood torefer to the same elements, features, and structures. The relative sizeand depiction of these elements may be exaggerated for clarity,illustration, and convenience.

DETAILED DESCRIPTION

The following detailed description is provided to assist the reader ingaining a comprehensive understanding of the methods, apparatuses,and/or systems described herein. Accordingly, various changes,modifications, and equivalents of the systems, apparatuses and/ormethods described herein will be suggested to those of ordinary skill inthe art. Also, descriptions of well-known functions and constructionsmay be omitted for increased clarity and conciseness.

FIG. 1 is a diagram illustrating an example of a system 10 forsummarizing contact center calls. The system 10 can be used by acustomer 100, an agent 200, and an analyst 300 to generate a summary ofa contact center call between the customer 100 and the agent 200.Referring to FIG. 1, a contact center call summarization system 10 mayinclude a customer communication device 110 such as a telephone,smartphone, tablet, or other electronic communication device, a network120 such as a phone or interne network to which the customercommunication device 110 is configured to connect, and a contact center210 which is a server/cloud configured to process the call with thecustomer communication device 110 through the network 120.

The contact center 210 may communicate with a speech-to-text generatingunit 220 which is configured to convert speech of a customercommunication into text, and the speech-to-text generating unit 220 maycommunicate with an intent recognizing unit 230 which is configured touse machine learning to match speech to intents and associated entities.The contact center call summarization system 10 may further include anagent user interface 240 which may be a communication device including adesktop or mobile or table application showing information to the agent,and is configured to communicate with each of the contact center 210,the speech-to-text generating unit 220, and the intent recognizing unit230. The contact center call summarization system 10 may further includean intent configuration unit 310 that can be used by the analyst 300 tocreate intents, entities, and associated training phrases for the intentrecognizing unit 230.

As already provided above, in one example, there are three end users ofthe contact center call summarization system 10—the customer, the agent,and the analyst.

In an example, the customer 100 places a call to, or receives a callfrom, the contact center. They do this via the customer communicationdevice 110, which connects their call through the network 120 to thecontact center 210. The agent 200 has a user interface 240, whichconnects to the contact center 210 for traditional contact centerfunctions like answering a caller, placing a caller on hold,transferring a caller, among other functions.

Still referring to FIG. 1, the audio stream generated during the callbetween the agent 200 and the customer 100 may be converted from speechto text, in real-time, using the speech-to-text generating unit 220. Thespeech-to-text generating unit 220 may use automated speech to texttechnologies such as off-the-shelf technology offered by Google,Microsoft, Amazon, IBM, among others.

The resulting real-time transcription may be fed into the intentrecognizing unit 230. In this example, the intent recognizing unit 230receives the transcribed speech in segments, and uses traditionalmachine learning algorithms to match the segments of the speech tointents and associated entities. The intents and entities may bepredefined. For example, an analyst 300 may utilize the intentconfiguration unit 310 to create predefined intents, entities, andassociated training phrases. For example, the intent configuration unit310 may use a tool such as Google's Dialogflow™, among other tools, togenerate predefined intents, entities, and training phrases. In thisexample, as the real-time transcribed text is sent to the intentrecognizing unit 230, it is matched with the predefined or pre-generatedintents and entities created by the analyst 300 and already communicatedto the intent recognizing unit 230 by the intent configuration unit 310.

In addition, the analyst 300 may create, for each intent, a mapping backto a sentence or sentences, which represent a good summary of theintent. The mapping may also include variable substitutions thatcorrespond to detected intents. For example, if an intent was“ProductReturn” and the one entity in the intent was “ProductName,” themapping may be as follows: “Customer states that they are unhappy with$ProductName and want to return it.” In this example, when the intent ismatched in real time, the intent recognizing unit 230 may use themapping and create a string of text that forms part of the call summary.This string of text can then be sent to the agent 200 by beingillustrated on the agent user interface 240. As new intents aredetected, more text strings may appended to the end of the call summary.Accordingly, a real-time, incrementally growing summary of the call isgenerated.

To ensure accuracy, the agent 200 can confirm and edit the results ofthe call summary using the agent user interface 240. For example, theagent 200 may be given the choice to confirm or edit a call summary,remove intents, text, or entire text strings from the call summary list,add intents, text, or entire text strings to the call summary list,change or update the value of an entity in the call summary, and reordertext or text strings in the call summary. These actions that may beperformed by the agent 200 using the agent user interface 240 aredescribed in further detail in reference with FIGS. 3-7. Once the agentis satisfied with the call summary, the agent can confirm the result.This confirmation ensures that the final summary is always accurate. Theresulting call summary is generated much faster than a manualagent-generated call summary while still ensuring uniformity ofstructure using a fixed mapping from intent to text. Further, in oneexample, the changes made by the agent 200 to the call summary may beused to adjust an AI model of the intent recognizing unit 230 to provideeven more accurate call summaries in a fully automated way.

It should be appreciated that the different units and/or devicesillustrated in FIG. 1, including the customer communication device 110,the network 120, the contact center 210, the speech-to-text generatingunit 220, the intent recognizing unit 230, the agent user interface 240,and the intent configuration unit 310, can be software executing on oneor more processors, such as shown in the computer/network drawingsdescribed in more detail below in reference to FIGS. 9 and 10.

FIG. 2 is a diagram illustrating an example of a user interface displaythat includes a call summary generated using the system 10 of FIG. 1.Referring to FIG. 2, an example of a user interface that illustrates acall summary 400 overlaying or side-by-side with a conversationtranscript 500. The call summary is generated by the contact center callsummarization system 10 describe above in reference with FIG. 1, and canbe illustrated on a display of the agent user interface 240 of thesystem 10.

FIGS. 3A, 3B, and 3C are diagrams illustrating examples of userinterfaces that allow an agent to confirm or edit a call summarygenerated using the system 10 of FIG. 1.

Referring to FIG. 3A, the call summary 400 and conversation transcript500 are again illustrated along with an “Edit Summary” button 410 and a“Confirm” button 420. In this example, the buttons 410, 420 are providedat the bottom of the user interface and may be provided in differentcolors. This alerts the agent that they are expected to edit and confirmthe summary. By providing a “Confirm” button, it is clear to the agentthat by pressing this button they are confirming the summary. Referringto FIG. 3B, hovering over the “Confirm” or “Edit Summary” buttons mayprovide more information for clarity such as clarifying that confirmingthe summary will add the summary to the Customer Relationship Management(CRM) system.

Referring to FIG. 3C, as an alternative or in addition to providing an“Edit Summary” button, an agent—after pressing the confirm button 420for a first time—may be provided with a dialog box 430 giving them theoption to edit the call summary if they have not previously edited thesummary. The dialog box may ask the agent to verify that the summary isaccurate, and may also present an option for showing a tutorial on howto edit the summary. In general and in some example, data on how oftenagents edit may be tracked. In one example, the dialog box 430 may popup more often if an agent is not making edits.

FIGS. 4A, 4B, 4C, and 4D are diagrams illustrating examples of userinterfaces that allow an agent to remove false positives in a callsummary generated using the system 10 of FIG. 1. Referring to FIGS. 4A,the call summary 400 and conversation transcript 500 are againillustrated. In this example, an agent may place a mouse pointer over atext segment in the call summary and immediately the text segment may behighlighted and the agent is prompted to remove the text segment bypressing a remove button 440. FIG. 4B illustrates the result of theagent moving the mouse pointer over another text segment; similarly,that segment is highlighted and another remove button 440 appearsadjacent the highlighted text. In FIG. 4C, the agent selects to removethe highlighted text by pressing the remove button 440, and in FIG. 4D,the highlighted text disappears along with the remove button. All textbelow the removed text may move upwards to make it clear that the oldtext was removed.

While this is only one example user interface for removing intents,text, or text segments in a call summary, other interfaces may be usedsuch as an agent double clicking a text segment to prompt an editfunction and pressing the delete key on a keyboard to remove the textentirely. In another example, the agent may be required to press on thetext, rather than hover over the text, to prompt the remove button. Inanother example, the agent may be required to drag and drop textsegments to a trash icon or area, among other examples of userinterfaces for removing text segments. In another example, a trash iconmay appear next to the text, and the agent clicks on the trash icon toremove the summary element.

FIGS. 5A-5H are diagrams illustrating examples of user interfaces thatallow an agent to update entities in a call summary generated using thesystem 10 of FIG. 1. Referring to FIG. 5A, an agent can move a mousepointer to anywhere over the text associated with an intent that has oneor more entities 450. When the text segment has an entity, an additionaltooltip 460, which may appears then fade away, may provide instructionsto the agent on how to edit the specific entity. The entity itself maybe highlighted in some way to help the agent know that this is theportion of the text segment being referred to for editing. In anexample, the entity may be highlighted in a different color, underlined,boxed, bolded, or distinguished from the remaining text in any otherway.

Referring to FIG. 5B, double clicking the entity 450 may prompt aseparate window 470 for editing the entity—in this example, a callbacknumber. The software may be programmed to recognize a phone number, andin turn, only allow numbers and special characters to be used in theediting window 470 for increased accuracy. Another tooltip 480 mayinstruct the agent to hit the return when done. Referring to FIG. 5C, anexample is illustrated after an agent changes the entity 450 in theediting window 470. Referring to FIG. 5D, after an agent presses returnto complete editing, the entity 450 is changed in the call summary andthe tooltip 480 fades away.

Referring to FIGS. 5E-5H, another example for editing an entity isillustrated. In this example and referring to FIG. 5E, an agent moves amouse pointer to anywhere over the text associated with an intent thathas one or more entities. The entity 450 itself is highlighted in someway as already described in reference with FIG. 5A. Referring to FIG.5F, in response to the agent moving the mouse point over the entity, theremove button disappears and an edit callback button 490 may appear. Asshown in FIG. 5G, pressing the edit callback button 490 may prompt theediting window 470 and tooltip 480 to appear like in FIG. 5C, andpressing return may complete the editing process as shown in FIG. 5H.

Because the interface already recognizes the type of entity, the editform may be custom based on the type of entity. For example, dates mayenable an NLP based date entry or calendar user interface entry. If anentity is an enumerated type, a dropdown list may be initiated includinga typedown select function.

FIGS. 6A, 6B, and 6C are diagrams illustrating examples of userinterfaces that allow an agent to reorder a call summary generated usingthe system of FIG. 1. Referring to FIG. 6A, when an agent moves a mousepointer over text, the remove button 440 appears but the agent maycontinue to press down and drag the text segment. Referring to FIG. 6B,dragging the text segment allows the text to pop out. A blue bar mayappear to indicate where the text will go if dropped. Referring to FIG.6C, a new location for the text segment may be selected, and the textmay be inserted into the new location and text segments below may slidedown.

FIGS. 7A, 7B, and 7C are diagrams illustrating examples of userinterfaces that allow an agent to add missing intents to a call summarygenerated using the system of FIG. 1. Referring to FIG. 7A, the removebutton 440 appears but the agent may continue to move the mouse pointerto a transition point between text segments. Referring to FIG. 7B, oncethe transition point is reached an add button 520 may be prompted or anycombination of a press or double clicking of the transition point willprompt the adding text function.

Referring to FIG. 7A, when the add text window 510 is prompted, an agentcan start typing text. Since the intents are a finite set, a dropdownmenu may use a typedown search. If the agent moves the mouse pointer tohover over text choices, the full text of the intent may be shown.Typedown can search intents over both the text of the phrase, as well askeywords which are associated with each intent. If the agent selects anexisting intent, it may be added and used to automatically update thetraining set for the associated intent. If the agent continues to typeand it is no longer a match for any text, the agent is adding freeformtext. The freeform text would be inserted into the summary, and anotification may be sent to an administrator that a new intent maypotentially need to be added. Alternatively, the agent can hit a +button at the bottom of the summary to add an intent, which produces thesame dropdown menu and text entry box. In this case, the intent is addedat the end of the summary. This eliminates the need for the agent tofigure out where in the summary to add the missing intent.

FIG. 8 is a diagram illustrating an example of a method for summarizingcontact center calls using the system of FIG. 1. Referring to FIG. 8, instep 605, a contact center communication device may receive or make acommunication with a customer device over a network. In step 610, aspeech-to-text generating unit may convert or transcribe speech of acustomer communication into text. In step 615, the speech-to-textgenerating unit may send speech to an intent recognizing unit. In step620, the intent recognizing unit uses machine learning in real-time toautomatically match speech to predetermined intents and associatedextracted entities. In step 625, a call summary is generated by mappingthe predetermined intents and extracted entities using one or moremapping functions and transmitted to an agent user interface which candisplay the call summary. In step 630, the transmitted call summary isedited by one or more of removing false positive text segments, intents,or entities in the call summary, updating entities in the call summary,reordering the call summary, or adding missing intents to the callsummary as described above in reference with FIGS. 3-7. In another step635, which may or may not occur repeatedly, a configuration unit mayupdate the intent recognizing unit with predetermined intents based oninput from an analyst or feedback from the editing in the agent userinterface.

FIG. 9 depicts an example diagram showing a system 700 for contactcenter call summarization. As shown in FIG. 9, the system 700 includes acomputing system 710 which contains a processor 720, a storage device730 and a contact center call summarization module 740. The computingsystem 710 includes any suitable type of computing device (e.g., aserver, a desktop, a laptop, a tablet, a mobile phone, etc.) thatincludes the processor 720 or provides access to a processor via anetwork 750 or as part of a cloud based application. The contact centercall summarization module 740 includes tasks (e.g., as described herein)and is implemented as part of a user interface module (not shown in FIG.9).

FIG. 10 depicts an example diagram showing an example computing system800 for contact center call summarization. As shown in FIG. 10, thecomputing system 800 includes a processor 810, memory devices 820 and825, one or more input/output devices 830, one or more networkingcomponents 840, and a system bus 850. In some embodiments, the computingsystem 800 includes the contact center call summarization module, andprovides access to the contact center call summarization module to auser as a stand-alone computer.

It should be understood that similar to the other processing flowsdescribed herein, the steps and the order of the steps in the flowchartdescribed herein may be altered, modified, removed and/or augmented andstill achieve the desired outcome. A multiprocessing or multitaskingenvironment could allow two or more steps to be executed concurrently.

While examples have been used to disclose the invention, including thebest mode, and also to enable any person skilled in the art to make anduse the invention, the patentable scope of the invention is defined byclaims, and may include other examples that occur to those of ordinaryskill in the art. Accordingly the examples disclosed herein are to beconsidered non-limiting. As an illustration, an athlete score and/or aranking of athletes may be generated using a number of different factorsor based on a single factor.

It is further noted that the systems and methods may be implemented onvarious types of data processor environments (e.g., on one or more dataprocessors) which execute instructions (e.g., software instructions) toperform operations disclosed herein. Non-limiting examples includeimplementation on a single general purpose computer or workstation, oron a networked system, or in a client-server configuration, or in anapplication service provider configuration. For example, the methods andsystems described herein may be implemented on many different types ofprocessing devices by program code comprising program instructions thatare executable by the device processing subsystem. The software programinstructions may include source code, object code, machine code, or anyother stored data that is operable to cause a processing system toperform the methods and operations described herein. Otherimplementations may also be used, however, such as firmware or evenappropriately designed hardware configured to carry out the methods andsystems described herein. For example, a computer can be programmed withinstructions to perform the various steps of the flowchart shown inFIGS. 3 and 12.

The systems' and methods' data (e.g., associations, mappings, datainput, data output, intermediate data results, final data results, etc.)may be stored and implemented in one or more different types ofcomputer-implemented data stores, such as different types of storagedevices and programming constructs (e.g., RAM, ROM, Flash memory, flatfiles, databases, programming data structures, programming variables,IF-THEN (or similar type) statement constructs, etc.). It is noted thatdata structures describe formats for use in organizing and storing datain databases, programs, memory, or other computer-readable media for useby a computer program.

The systems and methods may be provided on many different types ofcomputer-readable storage media including computer storage mechanisms(e.g., non-transitory media, such as CD-ROM, diskette, RAM, flashmemory, computer's hard drive, etc.) that contain instructions (e.g.,software) for use in execution by a processor to perform the methods'operations and implement the systems described herein.

The computer components, software modules, functions, data stores anddata structures described herein may be connected directly or indirectlyto each other in order to allow the flow of data needed for theiroperations. It is also noted that a module or processor includes but isnot limited to a unit of code that performs a software operation, andcan be implemented for example as a subroutine unit of code, or as asoftware function unit of code, or as an object (as in anobject-oriented paradigm), or as an applet, or in a computer scriptlanguage, or as another type of computer code. The software componentsand/or functionality may be located on a single computer or distributedacross multiple computers depending upon the situation at hand.

It should be understood that as used in the description herein andthroughout the claims that follow, the meaning of “a,” “an,” and “the”includes plural reference unless the context clearly dictates otherwise.Also, as used in the description herein and throughout the claims thatfollow, the meaning of “in” includes “in” and “on” unless the contextclearly dictates otherwise. Finally, as used in the description hereinand throughout the claims that follow, the meanings of “and” and “or”include both the conjunctive and disjunctive and may be usedinterchangeably unless the context expressly dictates otherwise; thephrase “exclusive or” may be used to indicate situation where only thedisjunctive meaning may apply.

1. A method for creating a textual summary of a call, comprising:transcribing speech to a text in real time using a speech-to-textgenerating unit configured for execution upon one or more dataprocessors; automatically matching, in real-time, the text topredetermined intents and extracted entities using an intent recognizingunit, which is directly coupled to the speech-to-text generating unitfor execution upon the one or more data processors; automaticallymapping the predetermined intents and extracted entities into a callsummary using one or more mapping functions; and displaying the callsummary using an agent user interface for execution upon the one or moredata processors, wherein the call summary is shown on the agent userinterface overlaying or side-by-side with the text.
 2. The method ofclaim 1, further comprising manually confirming the predeterminedintents and extracted entities of the call summary using the agent userinterface.
 3. The method of claim 1, wherein the automatically mappingof the predetermined intents and extracted entities comprises convertingthe predetermined intents and extracted entities into text strings, eachpredetermined intent mapping to a text string with variables,the-variables corresponding to one or more of the extracted entities. 4.The method of claim 3, further comprising generating the call summary bycreating a sequence in temporal order of the text strings.
 5. The methodof claim 1, further comprising removing false positive text segments,the predetermined intents, or the extracted entities in the call summaryusing the agent user interface.
 6. The method of claim 1, furthercomprising updating or editing text segments, the predetermined intents,or the extracted entities in the call summary using the agent userinterface.
 7. The method of claim 1, further comprising reordering textsegments, the predetermined intents, or the extracted entities in thecall summary using the agent user interface.
 8. The method of claim 1,further comprising manually adding text segments, other intents, orother entities to the call summary using the agent user interface. 9.The method of claim 1, further comprising manually or automaticallyupdating or creating intents, entities, and associated training phrasesbased on removals, updates, edits or reorderings performed in the agentused interface.
 10. A contact center call summarization system forgenerating a contact center call summary, comprising: a speech-to-textgenerating unit configured for execution upon one or more dataprocessors and configured to transcribe speech to a text in real-time;an intent recognizing unit, which is directly coupled to thespeech-to-text generating unit, for execution upon the one or more dataprocessors and configured to automatically match, in real-time, the textto predetermined intents and extracted entities and automatically mapthe predetermined intents and extracted entities into a call summaryusing one or more mapping functions; and an agent user interface forexecution upon the one or more data processors and configured to displaythe call summary, wherein the call summary is shown on the agent userinterface overlaying or side-by-side with the text.
 11. The contactcenter call summarization system of claim 10, wherein the agent userinterface is configured to allow manual confirmation of thepredetermined intents and extracted entities of the call summary. 12.The contact center call summarization system of claim 10, wherein theagent user interface is configured to automatically map thepredetermined intents and extracted entities by converting thepredetermined intents and extracted entities into text strings, eachpredetermined intent mapping to a text string with variables, thevariables corresponding to one or more of the extracted entities. 13.The contact center call summarization system of claim 12, wherein theagent user interface is further configured to generate the call summaryby creating a sequence in temporal order of the text strings.
 14. Thecontact center call summarization system of claim 10, where the agentuser interface is configured to allow manually removing false positivetext segments, the predetermined intents, or the extracted entities inthe call summary.
 15. The contact center call summarization system ofclaim 10, wherein the agent user interface is configured to allowmanually updating or editing text segments, the predetermined intents,or the extracted entities in the call summary.
 16. The contact centercall summarization system of claim 10, wherein the agent user interfaceis configured to allow manually reordering text segments, thepredetermined intents, or the extracted entities in the call summary.17. the contact center call summarization system of claim 10, whereinthe agent user interface is configured to allow manually adding textsegments, other intents, or other entities to the call summary.
 18. Thecontact center call summarization system of claim 10, further comprisingan intent configuration unit for execution upon the one or more dataprocessors and configured to update or create intents, entities, andassociated training phrases for the intent recognizing unit.
 19. contactcenter call summarization system for generating a contact center callsummary, comprising: a contact center communication device configured tocommunicate with a customer communication device via a network; aspeech-to-text generating unit configured for execution upon one or moredata processors and configured to convert speech of a customercommunication into text; an intent recognizing unit, which is directlycoupled to the speech-to-text generating unit, for execution upon theone or more data processors and configured to receive transcribed speechfrom the speech-to-text generating unit and use machine learning tomatch speech to intents and entities; an intent configuration unit forexecution upon the one or more data processors and configured to updateor create intents, entities, and associated training phrases for theintent recognizing unit; and an agent user interface for execution uponthe one or more data processors and configured to display a call summaryreceived from the intent recognizing unit to allow an agent to edit,replace, reorder, delete, or confirm text segments, intents, or entitiesof the call summary, wherein the call summary is shown on the agent userinterface overlaying or side-by-side with the text.
 20. The contactcenter call summarization system of claim 19, wherein the agent userinterface is further configured to allow the agent to: remove falsepositive text segments the intents, or the entities in the call summary;update or edit text segments, the intents, or the entities in the callsummary; reorder text segments, the intents or the entities in the callsummary; and add text segments, other intents, or other entities to thecall summary.